Automatic optimization in spectral Doppler ultrasound imaging

ABSTRACT

Methods and systems for automatic optimization in spectral Doppler ultrasound imaging are provided. The value for one or more spectral Doppler parameter is optimized using numerical optimization rather than predefined sampling. Various spectral Doppler parameters are set, such as a position of the gate, gate size, transmit frequency, filter settings, Doppler gain, beamline orientation or angle of intersection between the gate position and the scan line, aperture size, or other spectral Doppler transmit or receive parameters effecting the spectral Doppler imaging. A processor automatically calculates a setting or value for one or more of the spectral Doppler parameters, resulting in more objective optimization than provided by a user setting.

BACKGROUND

The present invention relates to spectral Doppler ultrasound. Inparticular, automatic optimization of spectral Doppler ultrasoundimaging is provided.

Spectral Doppler ultrasound imaging provides a two-dimensional image ofvelocities (vertical scale) values modulated by energy as a function oftime (horizontal scale) for studying fluid flow within a patient. Bytransmitting a plurality of pulses at a single gate location, a spectralDoppler response is generated in response to received echo signals.

Sonographers manually adjust the gate location, gate size, transmitfrequency and other spectral Doppler imaging control parameters in orderto acquire a desirable image. This process may be tedious and inexact,resulting in suboptimal spectral Doppler imaging. For example, thedesired location of the spectral Doppler gate is typically at a positionassociated with the maximum flow velocity. A user may inexactly positionthe range gate at a different, adjacent position. As another example, aninitial transmit frequency is selected by the user by adjusting thetransmit frequency to different values until the image is subjectivelycorrect, but not necessarily optimal.

Some processes have been proposed for automatic placement of thespectral Doppler gate. For example, a two-dimensional Doppler image ofenergy or velocity information is acquired. A position within thetwo-dimensional image associated with the maximum velocity or energy isselected for positioning of the spectral Doppler gate. Another proposedalgorithm also samples at a plurality of predefined locations. Inparticular, the spectral power is calculated at multiple predefinedlocations in a one, two or three-dimensional grid. The location with thegreatest spectral power is selected for the spectral Doppler gateposition. However, sampling at predefined locations, such as for atwo-dimensional image, may require extra processing and time.

Other spectral Doppler parameters may be automatically set, such as thesize of the gate, ideal line angle and point of origin on thetransducer.

BRIEF SUMMARY

The present invention is defined by the following claims, and nothing inthis section should be taken as a limitation on those claims. By way ofintroduction, the preferred embodiments described below include methodsand systems for automatic optimization in spectral Doppler ultrasoundimaging. The value for one or more spectral Doppler parameter isoptimized using numerical optimization rather than predefined sampling.Various spectral Doppler parameters are set, such as a position of thegate, gate size, transmit frequency, filter settings, Doppler gain,beamline orientation or angle of intersection between the gate positionand the scan line, aperture size, or other spectral Doppler transmit orreceive parameters effecting the spectral Doppler imaging. A processorautomatically calculates a setting or value for one or more of thespectral Doppler parameters, resulting in more objective optimizationthan provided by a user setting.

In a first aspect, a method for automatic optimization in spectralDoppler ultrasound imaging is provided. Multiple sequences of spectralDoppler pulses are fired into a patient. Multiple goal values aredetermined in response to the sequences. A change for a spectral Dopplerparameter is estimated as a function of the goal values. The spectralDoppler parameter is set automatically as a function of the estimatedchange.

In a second aspect, a method for automatic optimization in spectralDoppler ultrasound imaging is provided. An initial spectral Dopplerparameter value is received. The initial spectral Doppler parametervalue is automatically altered to a second spectral Doppler parametervalue. A third spectral Doppler parameter value is determined as afunction of a numerical optimization of the initial and second spectralDoppler parameter values.

In a third aspect, a method for automatic optimization in spectralDoppler ultrasound imaging is provided. At least one Doppler pulse isfired into an identified region. At least one of the transmit frequency,filter settings and Doppler gain are automatically set in response to anecho signal from the Doppler pulse.

In a fourth aspect, a system for automatic optimization in spectralDoppler ultrasound imaging is provided. The system includes a transduceroperative to fire sequences of spectral Doppler pulses. A processor isoperative to determine multiple goal values in response to thesequences, to estimate a change of the spectral Doppler parameter as afunction of the values and to automatically set the spectral Dopplerparameter as a function of the estimated change.

In a fifth aspect, a method for automatic optimization in spectralDoppler ultrasound imaging is provided. Multiple sequences of spectralDoppler pulses are fired into a patient. Multiple goal values aredetermined in response to the sequences. Based on these goal values,zero or more iterations of the following acts are generated adaptively,

-   -   generating an intermediate spectral Doppler parameter value        based on previous calculated goal values.    -   firing a sequence corresponding to this spectral Doppler        parameter value.    -   calculating the goal value in response to the sequence.        The resulting spectral Doppler parameter value is then        determined based on the preceding calculated goal values.

Further aspects and advantages of the invention are discussed below inconjunction with the preferred embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

The components of the figures are not necessarily to scale, emphasisinstead being placed upon illustrating the principles of the invention.Moreover, in the figures, like reference numerals designatecorresponding parts throughout the different views.

FIG. 1 is a block diagram of one embodiment of a system for automaticoptimization of spectral Doppler ultrasound imaging;

FIG. 2 is a flow chart diagram of one embodiment of a method forautomatic optimization of spectral Doppler ultrasound imaging;

FIG. 3 is a graphical representation of one embodiment associated withsetting a gate position and beamline orientation; and

FIG. 4 is a flow chart diagram of one embodiment of an adaptiveiterative process performed in the method of FIG. 2.

DETAILED DESCRIPTION OF THE DRAWINGS AND PRESENTLY PREFERRED EMBODIMENTS

Spectral Doppler parameters (e.g. imaging control parameters) areoptimally selected. The selection is automated to achieve differentimaging goals for different applications. For example, the spectrumintensity is maximized by setting the gate location and beamlineorientation. As another example, an area with the highest flow islocated for a gate position. As yet another example, a gate positionassociated with valve regurgitation is located. The desired goal isexpressed as a mathematical function to be optimized with respect to oneor more of the spectral Doppler parameter. For example, the spectralintensity sum, spectral signal-to-noise ratio sum, spectral maximumvelocity sum or other goal function is used to numerically optimize gatelocation, beamline orientation, transmit frequency, filter settings,Doppler gain, gate size, velocity baseline, scan line location, scanline angle or other spectral Doppler parameters.

FIG. 1 shows a system for automatic optimization in spectral Dopplerultrasound imaging. The system 10 includes a transmit beamformer 12, atransducer 14, a processor 16 and a display 18. Additional, different orfewer components may be provided. The system 10 is any now known orlater developed spectral Doppler ultrasound imaging system, such asultrasound systems manufactured by Siemens Medical Solutions USA, Inc.

The transmit beamformer 12 comprises a waveform generator, memory,digital signal processors, filters, delays, amplifiers, controlprocessors, other digital components, other analog components andcombinations thereof for generating sequences of Doppler pulses. Any nowknown or later developed transmit beamformer may be used. A transmitwaveform, such as a single cycle or multi-cycle bipolar square wave orsinusoidal waveform is generated for each of a plurality of channels inan aperture with relative delays and apodization for focusing theultrasound energy as a spectral Doppler pulse along a scan line.Unfocused or plane waves may also be generated. By setting any delays,apodization and aperture, the scan line position within a region may bechanged as well as the origin of the scan line from the transducer 14and angle of intersection of the scan line with the transducer 14. Thedelay and apodized waveforms generated by the transmit beamformer 12 areprovided to the transducer 14.

The transducer 14 comprises a one-dimensional, two-dimensional ormulti-dimensional transducer array of piezoelectric ormicroelectromechanical transducer elements. In alternative embodiments,a single element is provided for the transducer 14. The transducer 14 isoperative to fire sequences of spectral Doppler pulses by transducingthe electrical signals from the transmit beamformer into acousticalenergy. The transducer 14 converts electrical waveform signals from thetransmit beamformer 12 to acoustic energy for transmitting acousticenergy along a scan line. Some of the transmitted acoustic energyreflects off of structures and fluids. The reflected echoes areconverted by the transducer 14 into electrical energy and provided tothe processor 16.

The processor 16 comprises a receive beamformer, a spectral Dopplerdetector, a filter, amplifier, or other image processing device forconverting receive echo signals into a spectral Doppler image. Theprocessor 16 additionally or alternatively includes a control processorfor managing the system 10 or components of the system 10. In oneembodiment, the processor 16 comprises a digital signal processor, ageneral processor, an application specific integrated circuit, a digitalprocessor, an analog processor or any other processor now known or laterdeveloped. Additional, different or fewer components may be provided forthe processor 16.

In response to receive beamformed signals, Doppler detected signals, orimage signals generated for a spectral Doppler imaging display, theprocessor 16 determines goal values, such as a goal value associatedwith multiple sequences of Doppler pulses. For example, a sequence ofDoppler pulses is transmitted to generate information associated withone time for a spectral Doppler display, such as a velocity spectrummodulated as a function of energy for a given time. A goal value iscalculated from the spectrum information for that time. Another goalvalue is calculated in response to a subsequent sequence of pulses.Based on these two goal values, zero or multiple iterations of thefollowing acts are generated adaptively,

-   -   generating an intermediate spectral Doppler parameter value        based on previous calculated goal values.    -   firing a sequence corresponding to this spectral Doppler        parameter value.    -   calculating the goal value in response to the sequence.        The resulting spectral Doppler parameter value is then        determined based on the preceding calculated goal values.

The display 18 is a CRT, monitor, LCD, plasma screen, projector or othernow known or later developed display for displaying a spectral Dopplerimage responsive to the set parameters. For a black and white spectralDoppler image, a range of velocities with each velocity modulated as afunction of energy is provided as a function of time. The intensity of agiven pixel or pixel region represents energy where velocity is providedon the vertical scale and time provided on the horizontal scale. Otherimage configurations may be provided, including colorized spectralDoppler images.

FIG. 2 shows a method for automatic optimization in spectral Dopplerultrasound imaging. One or more spectral Doppler parameters arenumerically optimized. In one embodiment, the numerical optimizationoccurs without a full sampling of a one-, two-, or three-dimensionalregion. Only a few possible settings are sampled and a next possiblesetting is adaptively estimated or calculated. The spectral Dopplerparameter is set based on mathematical calculation rather thancomparison of multiple sampled settings. Various of the acts shown inFIG. 2 may be skipped, not provided or implemented in different ways.Additional or different acts may also be provided.

In act 30, an initial spectral Doppler parameter value is received. Thevalue is received from memory, a processor, user input or combinationthereof. For example, a user selects spectral Doppler imaging with aparticular transducer 14 to be used. In response, the system 10 providesvarious initial spectral Doppler parameter values, such as a transmitfrequency, gate size, filter settings and Doppler gain. As anotherexample, the user indicates a gate position on a two-dimensional imageand a processor determines transmit and receive beamformer settings fortransmitting to and receiving from the selected gate position. The useror the processor 16 determines an initial scan line angle or beamlineorientation relative to the selected gate position, such as the shortestline from the transducer 14 to the gate position or a line extendingperpendicular from the transducer 14 to the gate position. An initialvalue is provided for each of the spectral Doppler parameters or imagingcontrol parameters. Any of various users' settings, such as a gaincontrol setting in response to a gain control knob or otherconfiguration settings, provide the initial values. For example, theuser places the Doppler gate in a vicinity of flow or most likelylocation of maximum flow and presses a button to activate automaticoptimization. The initial settings correspond to the initially providedsettings, such as the Doppler gate position, provided by the user. Thesoftware or algorithm discussed herein guides the Doppler gate as wellas other spectral Doppler parameters to the proper depth and scan lineorientations so as to obtain an optimal spectrum. Additional algorithmperformance improvements can be achieved by restricting the valid searchregion for placing the Doppler gate to locations where color flowsignals have previously been detected, or to locations within the B modeimage which have intensities meeting threshold criteria. U.S. Pat. No.6,176,830, the disclosure of which is incorporated herein by reference,shows such improvements.

In act 32, the initial spectral Doppler parameter value for one or moreof the parameters is automatically altered to a different value. Thealteration occurs as part of a numerical optimization. In oneembodiment, an alteration predetermined for the type of parameter isprovided. For example, a transmit frequency is altered in a 1 MHz stepto be larger, but a different size step increasing or decreasing thefrequency may be provided. As another example, a gate position isshifted by one gate size along a same scan line or to an adjacent scanline. Any of various predetermined or experimentally determined shiftsand direction of a shift in each of the parameters or one of theparameters may be used. In other alternative embodiments, the shift sizeor direction are adaptive as a function of a value calculated in act 38for the initial spectral Doppler parameter value.

In act 34, multiple sequences of spectral Doppler pulses are fired. Onesequence is fired and a Doppler spectrum is determined in response tothe initial spectral Doppler parameter values. A subsequent or othersequence of Doppler pulses is fired, and a Doppler spectrum is generatedin response to the altered spectral Doppler parameter settings. Since atleast one setting for at least one spectral Doppler parameter isdifferent between the two firings, a different spectrum or differentspectral Doppler information may result. In alternative embodiments,information from prior to generation of the spectrum is acquired inresponse to the different settings. The firings are along a same ordifferent scan lines. In yet other alternative embodiments, a singlefiring of a Doppler pulse or a single sequence of Doppler pulses usedfor generating a single spectrum is provided without the alteration ofact 32 or only for the altered settings of act 32. A sequence of Dopplerpulses is provided for calculating or estimating the Doppler spectrum ata given time. Any number of transmitted pulses may be used for asequence, including different numbers of transmitted pulses forsequential sequences of Doppler pulses.

In one embodiment, a value for a single spectral Doppler parameter isaltered for optimization. In alternative embodiments, the values fortwo, more, a subset or all of the spectral Doppler parameters arealtered between two sequences of Doppler pulses. The sequences ofDoppler pulses may be separated by none, one or more other sequences ofDoppler pulses or other ultrasound pulses for any purpose.

A subsequent spectral Doppler parameter setting is determined as afunction of a numerical optimization of the initial and altered spectralDoppler parameter settings in act 36. In alternative embodiments, thesubsequent spectral Doppler parameter value is determined as a numericaloptimization of only the initial or only the altered spectral Dopplerparameter value. In yet other alternative embodiments, additionalalterations of one or more spectral Doppler parameters are provided fornumerically optimizing a given spectral Doppler parameter value. Byproviding numerical optimization, the amount of samplings to determinean optimum value is reduced. Any of various spectral Doppler parametersare optimized individually, sequentially, or in parallel.

To perform the numerical optimization of act 36, goal values aredetermined in response to the fired sequences of Doppler pulses of act34. For example, a resulting value responsive to the initial spectralDoppler parameter value is calculated, and another resulting valueresponsive to the altered spectral Doppler parameter value iscalculated. Goal values responsive to any of the various combinations ofsettings of spectral Doppler parameters are calculated.

The resulting or goal value is calculated from any of variousmathematical functions. In one embodiment, the resulting or goal valuesare calculated from a spectrum resulting from the firings and settingsof acts 30-34. Detected information or image gray scale values are used.In alternative embodiments, the resulting or goal values are calculatedfrom received data other than the calculated Doppler spectrum.

The goal value is calculated from a function to be optimized withrespect to the spectral Doppler parameters, such as gate location,beamline orientation, gate size, transmit frequency, filter settings orDoppler gain. One energy function is the spectral intensity sum or sumof intensity or energy values for non-noise velocities at a given timeor period. The spectral intensity sum is given by:

${{sis}( {{x1},{y1},\theta} )} = {\sum\limits_{v,t}^{\;}\;{{v}{G( {v,t} )}}}$where x and y provide the gate location, the θ is the beamlineorientation, v is the velocities and G(v, t) is the gray scale valuesfor each velocity at a given time. (v,t) are all the points inside thechosen velocity (min_v, max_v) and time duration (min_t, max_t) windowin the spectral display. The velocity may be squared or other spectralintensity functions may be used.

Another energy function is the spectral signal-to-noise ratio. Thesignal can be expressed as follows,

$\begin{matrix}{\sum\limits_{{({v,t})} \in X}^{\;}\;{G^{2}( {v,t} )}} \\{{num}\mspace{14mu}{of}\mspace{14mu}{elements}\mspace{14mu}{in}\mspace{14mu}{set}\mspace{14mu} X}\end{matrix}$where X is a set of (v,t) points inside the chosen time duration andvelocity window which has the value of G(v,t) greater than a certainthreshold. The noise information is acquired by image processing or byreceiving a frame of data without transmitting acoustic energy. Yetanother function is a spectral maximum velocity sum as shown below.

$\sum\limits_{t}^{\;}\;{\max( \lbrack {v:{v \in {{\lbrack {{min\_ v},{max\_ v}} \rbrack\mspace{20mu}{and}\mspace{14mu}{G( {v,t} )}} > {threshold}}}} \} )}$Means of energy, velocity or combination thereof are used in alternativeembodiments. Any of various functions which may be minimized, maximized,thresholded or otherwise used to identify an optimal setting may beused. For example, pattern matching of the energy as a function ofvelocity of the spectrum is used. Correlation or other pattern matchingalgorithms are performed to provide an amount of match.

The function used to determine the goal value is the same or differentfor different spectral Doppler parameters. In one embodiment, gatelocation, beamline orientation and gate size are optimized using thespectral intensity sum. The transmit frequency is optimized using thespectral signal-to-noise ratio sum to obtain a maximum energy as afunction of transmit frequency. The Doppler gain is set as a function ofthe spectral signal-to-noise ratio sum. The filter settings are alsooptimized as a function of the spectral signal-to-noise ratio sum. Forexample, the bandwidth of the clutter filter is altered to provide themaximum signal-to-noise ratio. Other filtering parameters for a clutterfilter or other filter may be optimized. Different combinations ofspectral Doppler parameter and optimization function are provided inother embodiments.

The function used for optimizing a particular spectral Doppler parameterdiffers in response to different types of spectral Doppler ultrasoundimaging. For example, the location of the gate is optimized as afunction of pattern matching for valve regurgitation imaging. A squareshaped spectrum of energy as a function of velocity identifies animproper valve regurgitation. The system 10 and associated spectralDoppler imaging parameters, such as the location of the gate, areoptimized to provide the spectrum most resembling a square shape so thatthe worse case is identified for comparison or diagnosis.

Goal values are calculated for a discrete time or over a time duration.For example, the spectral intensity sum is calculated for optimizing thegate position, beamline orientation and/or gate size over one or moreheart cycles. Different time periods may be used. In one embodiment, theheart cycle is calculated for identifying the time duration. In otherembodiments, a time period is selected that is associated with a typicalheart cycle. Other parameters for input to the optimization function maybe varied or set, such as the velocity window. In one embodiment, thevelocity window for identifying signal from noise in a spectral Dopplerimage is used. In other embodiments, a greater or lesser threshold isused for calculating the goal value.

In act 40, a new setting of the spectral Doppler parameter value isestimated. The setting is adaptively based on the calculated goalvalues. A change of the spectral Doppler parameter value or setting isestimated. The change is estimated either as a difference from a currentsetting or as an absolute value that is different than the currentsetting. The change is estimated for any one or more of the spectralDoppler parameters discussed above, such as transmit frequency, gateposition, filter settings, Doppler gain, angle of the scan line througha gate position (beamline orientation) and combinations thereof.

A numerical optimization searching technique is used to maximize thegoal values. In alternative embodiments, the goal value is minimized orotherwise thresholded. Any of various numerical searching techniques nowknown or later developed are used, such as in multi-dimensional case,Gradient Descent method, Conjugate Gradient method, Newton orQuasi-Newton method, in one dimensional case, Parabolic fitting method,Brent's method, Brent with first derivative method or Newton numericaloptimization. For example, rather than performing an exhaustive searchby sampling a plurality of locations within a region, as in GradientDescent method, a derivative is used to identify a likely value orsetting of the spectral Doppler parameter from previous settings. Agradient of the current setting provides a search direction of a futuresetting. If one of the altered settings of act 32 resulted in the goalvalue being worse, the setting is altered in an opposite direction. Asshown in FIG. 4, given the search direction, the numerical routineautomatically and iteratively generates zero or more immediate spectralDoppler parameter settings based on the goal values calculated with thepreceding settings. As a result of each numerical optimization, a goalvalue is calculated. The need for generating additional intermediatesettings of the Doppler parameter is determined, such as by comparisonto a threshold indicating an optimal setting. If no more intermediatesettings are to be calculated, then an optimal setting is estimated byselecting the setting associated with the desired goal value. Ifadditional intermediate settings are to be calculated, then the nextsetting is estimated from the numerical optimization. Pulses are firedusing the next setting and the process repeats by calculating anothergoal value. As a result, the optimal setting along the search directionis determined based on the preceding calculated goal values. When thedesired value is a maximum value, a negative representation may be usedto obtain minima for numerical searching techniques. In alternativeembodiments, only one of direction or magnitude is altered.

For example, the Doppler gate steering angle or beamline orientationvaries from −20 to 20 degrees. Starting at zero degrees, numericaloptimization may adjust the steering angle to maximum possible extent,such as −20 degrees in only 2, 3, 4, or any other low number ofiterations. An exhausted sub-sampling may require 40 samples at onedegree increments.

The new spectral Doppler parameter setting for one or more parameters isused to transmit and receive ultrasound energy. A goal value iscalculated based on the most recent information. The numerical searchingis then repeated to identify a next setting. The operation is repeateduntil a local maxima or local minima is identified. In alternativeembodiments, a threshold is applied to the magnitude of change toindicate a sufficient maxima or minima without identifying an exactmaxima or minima setting. Other algorithms may be used for ending thenumerical optimization, such as a reversal of direction in thederivative or gradient associated with a sufficiently small magnitudechange.

In one embodiment, the gradient direction is associated with atwo-dimensional plane, such as for the gate position. Three or more goalvalues and associated initial and alternate settings may be used toprovide a two-dimensional gradient direction or vector. Other values,such as the beamline orientation, transmit frequency, Doppler filtersettings, and Doppler gain, are numerically optimized using initiallytwo or more different settings. For three-dimensional imaging,additional settings may be used for gate position numericaloptimization.

In one embodiment, the spectral Doppler parameters are numericallyoptimized sequentially. For example, a gate location or position isoptimized, and then the beamline orientation or angle of incidence tothe gate location is optimized subsequently. The parameters areoptimized in any of various possible orders.

In alternative embodiments, two or more spectral Doppler parameters areoptimized substantially simultaneously, such as using an energy or goalfunction that depends on two different spectral Doppler parameters. Forexample, the gate depth and beamline orientation relative to the gatelocation (i.e. angle of incidence) are optimized as part of the samefunction. An initial depth and orientation are received. A sample isthen acquired at a different depth with the same orientation, and asubsequent sample is obtained with a different orientation but a samedepth as the initial depth. The spectral intensity sum is calculated foreach of the three samples. The derivative or gradient associated witheach of the parameters is calculated and provides one axis of atwo-dimensional vector representation. The resulting gradient directionprovides a search direction for a better gate depth and orientationsetting. Zero or multiple iterations of steps generate, adaptively,which includes generating intermediate settings along the searchdirection and calculating the corresponding goal value as part of thenumerical optimization. Then, the optimal setting along the searchdirection can be determined based on the preceding calculated goalvalues. To further optimize the setting, the above process is repeatedto obtain a new gradient direction at the current best setting and thusdetermine the next best setting. In the above example, the gradientprovides a search direction of a desired setting for each of the gatedepth and orientation in a two-dimensional space corresponding to gatedepth and orientation. The two-dimensional vector identifies asubsequent gate position and orientation as part of the numericaloptimization. Other vector processes may be used. Multivaried functionsaccounting for two or more spectral Doppler parameters is numericallyoptimized without requiring subsampling of predefined locations using aplurality of different settings and combinations. Energy or goalfunctions that are a multiplication, addition, subtraction, division orother mathematical combination of information associated with twodifferent parameters may be used.

FIG. 3 shows an initial gate position 50 associated with a scan line 52perpendicular to the transducer 14. As part of either sequential orsimultaneous sampling for numerical optimization, the gate position isshifted to a position shown at 54 along a different scan line 56. Thebeamline orientation or angle of incidence to the gate position 50 isalso shifted as represented by scan line 58. Using numericaloptimization, the gate position may be determined as position shown at60 along the same scan line 52 that is normal to the transducer 14.Other positions and scan line orientations may be provided.

Altering settings of one spectral Doppler parameter are used to set adifferent spectral Doppler parameter in one embodiment. For example, thebandwidth of a clutter filter is set by altering the beamlineorientation or angle of incidence. A spectrum is obtained for twodifferent angles of incidence. The two spectra are compared. Thebandwidth of the filter is set at a frequency associated with thedivergence on the low frequency end of the spectra from each other. Thesimilar low frequency information represents clutter to be filtered out.Where only flow information is available in each spectra, the spectramay be different for all low frequencies. As a result, the bandwidth ofthe Doppler clutter filter is set to zero or the low frequency noise cutoff of the spectra.

In act 42, the spectral Doppler parameter is set as a function of theestimated change from the numerical optimization. The processor 16 setsthe spectral Doppler parameter without user input other than an initialsetting. The numerical optimization is also performed automatically. Theresulting value is used for subsequent imaging or further numericaloptimization. Where more than one spectral Doppler parameter is beingset sequentially, the process automatically repeats until some or allspectral Doppler parameters have been set. Where two or more spectralDoppler parameters are set substantially simultaneously, such as afunction of a vector, the final vector identifying a maxima, minima orsufficiently close maxima or minima identifies the final settings of thespectral Doppler parameters. The final setting of the spectral Dopplerparameters is the same or different than the initial or any subsequentsettings. For example, a numerical optimization may follow a trend in asetting to the maxima and then determine the additional sample orsamples following a trend away from the maxima in order to identify themaxima. As another example, the initial user settings may correctlyidentify the maxima as confirmed by numerical optimization.

In act 44, a spectral Doppler display is generated using theautomatically set spectral Doppler parameter values. A spectral Dopplerimage is generated during the numerical optimization in response to thevarious settings in one embodiment, but may be generated only after thesettings are numerically optimized in other embodiments. Alternatively,the initial settings are used for generating a spectral Doppler imageuntil numerically optimized settings are available.

The optimized spectral Doppler parameter settings are used for animaging session or until the user resets one or more of the imagingcontrols affecting a spectral Doppler parameter setting. In alternativeembodiments, one, a subset or all of the spectral Doppler parameters areoptimized periodically regardless of user input or are optimized inresponse to a user request for optimization. Any of various periods maybe used, such as every heart cycle, every second, or every minute.Optimization is triggered in other embodiments by events, such as thedetection of tissue movement relative to the transducer, a heart cycleevent, a breathing cycle event, or other detected parameter.

Automatic optimization of spectral Doppler parameters for ultrasoundimaging are provided in another embodiment with or without numericaloptimization. At least one Doppler pulse is fired into an identifiedregion. A sequence of Doppler pulses associated with determining aspectrum at one time or a plurality of sequences of Doppler pulses maybe used. The region is identified by a user by positioning a region ofinterest, identifying a range gate position or by positioning atransducer relative to the patient. The system may identify a regionusing numerical optimization, thresholding, border detection or otherfluid detection algorithms and devices. Transmit frequency, filtersettings or Doppler gain are automatically set in response to echosignals from the firing. The automatic setting is responsive tonumerical optimization, sampling and comparison, or other now known orlater developed optimization techniques. In one embodiment, numericaloptimization is used so that the setting is estimated from one or moreprevious settings using a numerical function. The Doppler parameter oftransmit frequency filter setting or Doppler gain is automatically setas a function of the estimated setting. In alternative embodiments,sample and comparison is used where a region is sampled or subsampled atpredefined values and resulting values associated with each location orpossible variation of the spectral Doppler parameter are compared toidentify a maxima or minima value without numerical optimization.

As an alternative to a gradient or vector based numerical optimization,a numerical optimization using optimized search patterns may be used.For example, a plurality of locations around an initial setting aresampled. The maxima or minima of the sample locations is selected and asearch is then repeated using the new setting. As yet anotheralternative, a subsampling with one magnitude or spacing is provided.Lesser magnitude changes are then implemented as the process repeats foreach identified maxima or minima. These refined searching techniquesprovide numerical optimization without using a mathematical formula forestimating the change in a setting. The change in a setting is estimatedby the search pattern.

While the invention has been described above by reference to variousembodiments, it should be understood that many changes and modificationscan be made without departing from the scope of the invention. It istherefore intended that the foregoing detailed description be regardedas illustrative rather than limiting, and that it be understood that itis the following claims, including all equivalents, that are intended todefine the spirit and scope of this invention.

1. A method for automatic optimization in spectral Doppler ultrasoundimaging, the method comprising: (a) firing at least first and secondsequences of spectral Doppler pulses; (b) determining at least first andsecond goal values in response to the first and second sequences,respectively; (c) estimating a change of a spectral Doppler parameterfrom the first and second goal values; and (d) automatically setting theoptimal spectral Doppler parameter as a function of the estimatedchange; wherein (a) comprises transmitting the first sequence inresponse to a first setting of the spectral Doppler parameter andtransmitting the second sequence in response to a second setting of thespectral Doppler parameter, the first setting different than the secondsetting, and (d) comprises automatically setting the spectral Dopplerparameter at a third setting the same or different than one or both ofthe first and second settings.
 2. The method of claim 1 wherein (c)comprises estimating the change of the spectral Doppler parameterselected from the group of: transmit frequency, gate position, filtersetting, Doppler gain, angle of scan line for a gate position andcombinations thereof and (d) comprises automatically setting thespectral Doppler parameter selected from the group above for (c).
 3. Themethod of claim 2 wherein (c) comprises estimating the change of thegate position and wherein (d) comprises automatically setting the gateposition.
 4. The method of claim 2 wherein (c) comprises estimating thechange of the Doppler gain and wherein (d) comprises automaticallysetting the Doppler gain.
 5. The method of claim 2 wherein (c) comprisesestimating the change of the filter setting and wherein (d) comprisesautomatically setting the filter setting.
 6. The method of claim 1wherein (b), (c) and (d) comprise numerically optimizing the spectralDoppler parameter without full sampling of a one or higher dimensionalregion.
 7. The method of claim 1 further comprising: (e) generating aspectral Doppler display in response to the spectral Doppler parameterset in act (d).
 8. The method of claim 1 wherein (c) comprisesestimating a vector corresponding to two different spectral Dopplerparameters and (d) comprises setting both spectral Doppler parameters asa function of the vector.
 9. The method of claim 1 wherein (b) comprisesdetermining the first and second goal values as spectral intensity sums.10. The method of claim 1 wherein (b) comprises determining the firstand second goal values as spectral signal-to-noise sums.
 11. The methodof claim 1 wherein (b) comprises determining each of the first andsecond goal values over at least a one heart cycle period, the firstgoal value corresponding to a different heart cycle than the second goalvalue.
 12. The method of claim 1 wherein (c) comprises adaptivelyperforming zero or more iterations of the following acts based on thefirst and second goal values; (c1) generating an intermediate spectralDoppler parameter setting based on previous calculated goal values; (c2)firing a sequence corresponding to the intermediate spectral Dopplerparameter; and (c3) calculating a third goal value in response to thesequence; and wherein (d) comprises automatically setting the optimalspectral Doppler parameter based on the preceding calculated goalvalues.
 13. A method for automatic optimization in spectral Dopplerultrasound imaging, the method comprising: (a) firing at least twoDoppler Pulses into an identified region; (b) automatically settingtransmit frequency, filter settings or combinations thereof in responseto an echo signal from (a); and (c) estimating a first setting fromprevious settings, at least one of the previous settings being differentfrom another of the previous settings; wherein (b) comprisesautomatically setting as a function of the estimated first setting. 14.A system for automatic optimization in spectral Doppler ultrasoundimaging, the system comprising: a transducer operative to fire at leastfirst and second sequences of spectral Doppler pulses, the firstsequence being different from the second sequence; and a processoroperative to determine at least first and second values in response tothe first and second sequences, respectively, estimate a change of aspectral Doppler parameter as a numerical optimization function of thefirst and second values, and automatically set the spectral Dopplerparameter as a function of the estimated change.
 15. The system of claim14 wherein the processor is operative to estimate the change byadaptively generating zero or more of iterations of acts which includeone or more of: generating intermediate spectral Doppler parametersetting based on the preceding calculated values, to instruct thetransducer to fire the corresponding sequence of spectral Doppler pulsesand compute the intermediate goal value, and to automatically set theoptimal spectral Doppler parameter value based on the precedingcalculated values.
 16. A method for automatic optimization in spectralDoppler ultrasound imaging, the method comprising: (a) firing at leastfirst and second sequences of spectral Doppler pulses, the firstsequence being different from the second sequence; (b) determining atleast first and second goal values in response to the first and secondsequences, respectively; (c) adaptively performing zero or moreiterations of the following acts based on the first and second goalvalues; (c1) generating an intermediate spectral Doppler parametersetting based on previous calculated goal values; (c2) firing a sequencecorresponding to the intermediate spectral Doppler parameter; and (c3)calculating a third goal value in response to the sequence; and (d)automatically setting an optimal spectral Doppler parameter based on thepreceding calculated goal values.